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Cited by 10Advanced Bandit Algorithms ResearchAdvanced Multi-Objective Optimization AlgorithmsGaussian Processes and Bayesian Inference

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Generalized hierarchical expected improvement method based on black-box functions of adaptive search strategy

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Zhang, Lulu, Jin, Guang, Liu, Tianyu, Zhang, Ran·2022·Applied Mathematical Modelling
DOI 10.1016/j.apm.2021.12.041
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Research works printed but not linked: 24

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  17. Chen, 2019, A hierarchical expected improvement method for bayesian optimization, eprint arXiv:1911.07285 · arXiv
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Metadata

Authors
Zhang, L., Jin, G., Liu, T., & Zhang, R.
Affiliations
National University of Defense Technology (CN)
Corresponding author
Jin, Guang
ORCID
Venue
Applied Mathematical Modelling
Publisher
Elsevier BV
Published
2022-06
Volume
106
Pages
30-44
ISSN
0307-904X (ISSN-L)
DOI
10.1016/j.apm.2021.12.041
OpenAlex
W4206983367
Cited by
10
References
0
Citations by year
2026: 1 · 2025: 3 · 2024: 4 · 2023: 1 · 2022: 1
FWCI
1.38
Type
journal article
Language
en
Open access
Licence
Locations
Applied Mathematical Modelling (publishedVersion)
Topics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Advanced Bandit Algorithms Research
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Advanced Multi-Objective Optimization Algorithms
  • Physical Sciences › Computer Science › Artificial Intelligence › Gaussian Processes and Bayesian Inference
Keywords
Bayesian optimization, black-box functions, adaptive search strategy, acquisition functions, hierarchical Gaussian process, hyperparameter estimation, basis function selection, surrogate-based optimization

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